Lo que serás capaz de hacer

This course contains the use of artificial intelligence. Master Amazon Bedrock AgentCore and build production-ready AI agents in just 6 hours. This comprehensive course takes you from zero to deploying intelligent, multi-agent systems that integrate with real enterprise tools—all using AWS's newest agentic AI platform. Whether you're an enterprise developer rushing to deploy AI agents in production, or a seasoned AWS engineer transitioning into agentic AI, this course gives you everything you need to build sophisticated AI systems that actually ship to production. What You'll Learn - Foundation & Core Services: AgentCore Quick Start – Deploy your first intelligent agent in 15 minutes using Amazon Bedrock AgentCore Runtime Integration – Master ANY agent framework: Strands, LangGraph, CrewAI, or custom Python implementations AgentCore Gateway – Connect agents to MCP servers, third-party APIs, and internal tools with secure credential management AgentCore Memory – Implement conversation history, long-term memory, and context-aware agents that remember user preferences AgentCore Identity – Handle OAuth flows, API key management, and IAM integration for secure, multi-user agent systems AgentCore Observability - Leverage the Amazon CloudWatch GenAI Observability Dashboard and integrate with 3rd Party tools via OpenTelemetry AgentCore Code Interpreter – Let agents write and execute Python code dynamically for data analysis and computation AgentCore Browser Tools – Enable agents to navigate websites, extract data, and interact with web applications autonomously AgentCore Evaluation – Measure, validate, and benchmark your agents with production-grade evaluation workflows AgentCore Policy – Apply fine-grained guardrails to control what your agents can and can't do in production Hands-On Learning: 10+ Production Labs This isn't just lectures—you'll build real applications through comprehensive, step-by-step labs: Lab 0: Setup your AWS Account, Amazon Kiro and use the AWS Free Tier Lab 1: AgentCore Runtime – Deploy your first Bedrock AgentCore Runtime agent with Strands SDK and Claude Sonnet, test locally, and understand the core architecture. Lab 2: Gateway – Connect your agent to real-world Weather, Flight and Exchange rate API sources using MCP and AgentCore Gateway with API Key authentication. Lab 3: Memory – Build a customer service agent with conversation history, user profile memory, and context-aware responses across sessions. Lab 4: Identity & OAuth – Implement secure 3LO OAuth agents with Google OAuth to create documents in your Google Drive, credential management, and per-user data isolation. Lab 5: Code Interpreter Tools – Create a data analysis agent that writes Python code, generates visualizations, and performs statistical analysis on user data. Lab 6: Browser Tools – Build a research agent that navigates websites, extracts information, and compiles reports automatically. Lab 7: Integrate everything into one Agent - Create one AgentCore Runtime Agent that connects to Gateway with all MCP Tools for weather, flight and exchange rate. Lab 8: AgentCore Observability – Instrument your agents with CloudWatch GenAI Dashboard and OpenTelemetry for full production visibility Lab 9: AgentCore Evaluation – Run evaluations on your agents to measure quality, catch regressions, and validate behavior before shipping Lab 10: AgentCore Policy – Deploy fine-grained policies that control agent behavior in production environments

Tu certificado lo emite la SEP, no solo una plataforma

Al demostrar la competencia recibes un certificado emitido por la Secretaría de Educación Pública a través del Gobierno del Estado de México: un documento oficial que puedes presentar con confianza ante cualquier empleador o institución.

Tu itinerario, de la inscripción al certificado

Un certificado oficial de la SEP

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